Energy Consumption of Neural Networks on NVIDIA Edge Boards: an Empirical Model

4 October 2022

Papers citing "Energy Consumption of Neural Networks on NVIDIA Edge Boards: an Empirical Model"

6 / 6 papers shown

Title
Kernel-Level Energy-Efficient Neural Architecture Search for Tabular Dataset Hoang-Loc La Phuong Hoai Ha 37 0 0 11 Apr 2025
Neuromorphic force-control in an industrial task: validating energy and latency benefits Camilo Amaya Evan Eames Gintautas Palinauskas Alexander Perzylo Yulia Sandamirskaya Axel von Arnim 42 0 0 13 Mar 2024
A Comparative Study of Machine Learning Algorithms for Anomaly Detection in Industrial Environments: Performance and Environmental Impact Álvaro Huertas-García Carlos Martí-González Rubén García Maezo Alejandro Echeverría Rey 24 3 0 01 Jul 2023
Divide and Save: Splitting Workload Among Containers in an Edge Device to Save Energy and Time A. Khoshsirat Giovanni Perin M. Rossi 26 4 0 13 Feb 2023
Energy Efficient Deployment and Orchestration of Computing Resources at the Network Edge: a Survey on Algorithms, Trends and Open Challenges N. Shalavi Giovanni Perin Andrea Zanella M. Rossi 24 6 0 28 Sep 2022
Pruning and Quantization for Deep Neural Network Acceleration: A Survey Tailin Liang C. Glossner Lei Wang Shaobo Shi Xiaotong Zhang MQ 150 674 0 24 Jan 2021